Timor-Leste
GDP per capita to 2060, by scenario
Constant-rate scenario path; the 2060 endpoint levels are illustrative, not forecasts.
Factor profile
These economies supply copper, fuels, bauxite, iron ore, uranium and other inputs required for the build-out.
How this economy meets AI
Today’s production, workforce and automation baseline — context for the scenarios, outside the AGI Growth Index.
Where output comes from (% of GDP)
Where people work (% of employment)
Informal employment
Current automation exposure
Production and exports are resource-led. Direct workplace exposure may be limited, while global demand, commodity prices, extraction productivity and ownership of the resulting capital still transmit AI’s effects.
This country is not covered by the Global Automation Atlas’s public country file; its task-level exposure work for other countries is at automationatlas.org.
Sources: World Bank WDI; ILOSTAT; Global Automation Atlas (Garg, Crosta & Baier, 2026). The latest available year is shown for each measure; vintages differ, so shares may not sum to 100.
Where Timor-Leste starts
Timor-Leste sits in the resource suppliers group, the countries that sell the build-out its raw inputs. It is the odd member. Most resource suppliers have some infrastructure to build on; Timor-Leste has almost none. Physical build speed scores 1 out of 5, compute and energy access 1, AI diffusion 1.1 — all near the floor. Its one high mark is catch-up headroom, 4.4: it starts so far back that the room to grow is vast. The strengths are real but narrow. Oil and gas fund the state through the Petroleum Fund, one of the region's best-run sovereign wealth funds, and fuel made up 67% of exports. The binding constraints are power, connectivity and skills. At about $1,341 GDP per person, this is a lower-income country. Ten-year trend growth is 1.5% a year.
The three paths
These are simulations, not forecasts. The Modest path is the baseline; the two AGI scenarios fork from it. Under the Modest scenario, AI stays a normal technology. Timor-Leste would hold near trend at 1.5% growth a year, 133rd of 157. Its economy would keep leaning on gas revenue and the Petroleum Fund. Under Gradual takeoff, growth would climb slowly over two decades and reach 1.9% a year once AGI matures around 2045, ranking 156th, second from the bottom of the table. Under Fast takeoff, growth would reach 1.6% a year from the early 2030s, again 156th. The rates barely move because a takeoff rewards compute, energy and skills, and Timor-Leste holds almost none of them. Its large catch-up headroom stays locked without those inputs. However fast its neighbors grow, Timor-Leste would be left behind unless the enabling pieces arrive. Politics could slow or redirect any of these paths. How Timorese and their government respond to transformative AI is a variable the model holds constant.
How you would know which world you are in
The scenarios look almost the same until about 2030. Watch leading indicators, not GDP, and watch them live. Three global signals matter most. First, whether the METR task horizon curve keeps doubling every four to five months through 2027–28; METR publishes it at metr.org. Second, whether frontier lab revenue and capital spending keep compounding; Epoch AI tracks both at epoch.ai. Third, whether growth in the ten to twenty most-ready economies — the United States and China above all — breaks above trend in the early 2030s. Double-digit growth there within a couple of years of 2030 would signal a fast world. A point or two above trend by the mid-2030s would signal a gradual one. A fade back to trend would signal a modest one. Timor-Leste's own signals would arrive earlier than the growth data: a final investment decision on the Greater Sunrise gas field, the landing of a submarine internet cable, and steady progress on ASEAN accession.
If growth goes explosive
For Timor-Leste, growth would not go explosive at all. At 1.6% a year under Fast, it would fall far behind a frontier compounding at 39.2% and a regional median near 16%. That is relative decline, not catch-up: the world would race ahead while Timor-Leste held near its own history. Say it plainly — the model shows AGI largely passing this country by unless it changes the inputs. The economy would stay small and gas-dependent. The honest downside is the Petroleum Fund itself. If an AGI-driven world speeds the shift away from fossil fuels, gas revenue could be repriced downward just as the fund is drawn down, leaving the state without its main income. The hedge is to convert the rents now, into power, skills and connectivity, rather than spend them on consumption. Timor-Leste's young workforce sends labor abroad, to Australia and Korea; faster growth and higher wages at home would ease the pressure to emigrate. The stress test lands on the state: on the Petroleum Fund's managers, the ministries that permit and procure, and the ports that connect the country at all.
What Timor-Leste can do now
Three levers follow from the scores, and two pay off whether or not AGI arrives. The first is AI diffusion capacity, at 1.1. Digital skills, permissive deployment rules and digitized government services carry weight even in the skeptic's world, so building them is a no-regret move, and Timor-Leste starts from nearly a blank slate. The second is physical build speed, at 1. Faster permitting, pre-zoned land and transmission built ahead of demand help under every scenario; they are the base any energy or data center project would need. That too is no-regret. The third lever is the bet: compute and energy access, at 1. It barely moves growth if AI stays ordinary, and only modestly even under a fast takeoff here, but it carries the most weight of the three. Closing it means turning gas and land into reliable power. Chile shows one path: it launched a National Data Center Plan to pair its clean power with hyperscale investment. A cautious government can act on the two no-regret levers today and lose nothing if the skeptics are right. Open the atlas's policy editor to test how these scores reshape Timor-Leste's path.
Use the policy editor to test how different factor scores change Timor-Leste’s modeled path. The roadmap builder below can then incorporate those targets into a 1,000-day planning prompt.
Drafted with Claude, Anthropic’s AI model, from the atlas’s data and an editorial template set by the author.
Create a 1000-day AGI and growth roadmap prompt
This prompt can be used with Claude, ChatGPT or an open-weight model hosted on your institution’s systems. It includes the atlas material for Timor-Leste: the country brief, economic structure, region, archetype and global scenarios. It instructs the model to ask for local information, use existing strategies and the political calendar, and preserve the atlas’s interpretation rules. The prompt is assembled in your browser; the information entered here is not sent elsewhere.
1 · Read the brief → 2 · Set targets in the policy editor → 3 · Generate and copy the prompt → 4 · Run it with an approved model, with high reasoning effort and web access where permitted
Instructions are generated in the selected language; the data annex remains in English. Translations are machine-drafted, and corrections from native speakers are welcome through the contact links on the start page.